title: Clinical data extraction and feedback in general practice: a case study from Australian primary care.
abstract: BACKGROUND
  Quality improvement in general practice has increasingly focused on the analysis of its clinical databases to guide its improvement strategies. However, general practitioners (GPs) need to be motivated to extract and review their clinical data, and they need skills to do so. This study examines the initial experience of 15 practices in undertaking clinical data extraction and management and the support they were given by their local division of general practice.
  
  
  OBJECTIVE
  To explore the uptake of data extraction tools in general practice and understand how divisions of general practice can assist with their uptake.
  
  
  METHODS
  This study was conducted within a single division of general practice within the south-eastern suburbs of metropolitan Melbourne, Australia. Self-selected practices were offered a data extraction program ('tool') free of charge, with ongoing division support. Practice representatives, either GPs, practice nurses or other practice staff members, were given instructions on how to extract data using the data extraction tool. This was followed by discussion with division staff regarding which clinical areas might be focused on. Division staff systematically recorded information about the experience of the practices and collated their clinical data.
  
  
  RESULTS
  Fifteen practices, representing 69 GPs, participated. The practices chose from the following areas to work on as quality improvement activities: improving data entry; inactivating patient files for those who no longer attended the practice; correcting demographic information; diabetes and coronary heart disease management. The recording of data, according to the extraction tool, was found to be incomplete. For example, one-third of the patients who had HbA1cs recorded were on target, i.e. <7%, but nearly half the patients with diabetes did not have HbA1cs recorded at all. About half the patients with coronary heart disease were not reported as taking aspirin and one-third were not on a statin. Nearly half the patients who had attended their practice in the previous 30 months did not have smoking status recorded.
  
  
  CONCLUSIONS
  While data extraction programs provide GPs with useful tools for examining their clinical databases and identifying clinical practice issues which could be improved, external support, such as that provided by divisions, is helpful. Technical barriers, such as the failure of extraction tools to recognise some data and the failure to comprehensively enter data, are impediments, but in spite of these considerable interest exists in the use of clinical data to improve practice.
authors.affiliation: Monash Division of General Practice, East Bentleigh, Victoria, Australia. Peter.Schattner@monash.edu
authors.forename: Peter
authors.initials: P
authors.lastname: Schattner
authors.forename: Mary
authors.initials: M
authors.lastname: Saunders
authors.forename: Leslie
authors.initials: L
authors.lastname: Stanger
authors.forename: Michele
authors.initials: M
authors.lastname: Speak
authors.forename: Kate
authors.initials: K
authors.lastname: Russo
mesh_terms: D001241:Aspirin / Q000008:administration & dosage; D001315:Australia; D003327:Coronary Disease / Q000628:therapy; D003920:Diabetes Mellitus / Q000628:therapy; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000008:administration & dosage; D016247:Information Storage and Retrieval / Q000706:statistics & numerical data*; D007256:Information Systems / Q000458:organization & administration*; D011320:Primary Health Care / Q000458:organization & administration* / Q000592:standards; D058996:Quality Improvement / Q000458:organization & administration* / Q000592:standards
chemical_list: D001241:Aspirin; D006442:Glycated Hemoglobin; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors